ArticleJournal of the Korean Statistical Society2009
Why Do We Test Multiple Traits in Genetic Association Studies?
Article in Journal of the Korean Statistical Society, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Pooled it
- Research on multi-trait genome association study method based on Shannon information entropy.BMC bioinformatics · 2026Article
- Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background.Molecular breeding : new strategies in plant improvement · 2024Article
- Multiple phenotype association tests based on sliced inverse regression.BMC bioinformatics · 2024Article
- Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study.Nature communications · 2024Article
- Maize green leaf area index dynamics: genetic basis of a new secondary trait for grain yield in optimal and drought conditions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Quantitative trait locus mapping analysis of multiple traits when using genotype data with potential errors.PeerJ · 2021Article
- Bayesian multivariate reanalysis of large genetic studies identifies many new associations.PLoS genetics · 2019Article
- Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence.The annals of applied statistics · 2018Article
- Estimates of genomic heritability and genome-wide association study for fatty acids profile in Santa Inês sheep.BMC genomics · 2018Article
- Statistical Analysis of Multiple Phenotypes in Genetic Epidemiologic Studies: From Cross-Phenotype Associations to Pleiotropy.American journal of epidemiology · 2018Review
- Simultaneous estimation of QTL parameters for mapping multiple traits.Journal of genetics · 2018Article
- Inference on phenotype-specific effects of genes using multivariate kernel machine regression.Genetic epidemiology · 2018Article
- A method for analyzing multiple continuous phenotypes in rare variant association studies allowing for flexible correlations in variant effects.European journal of human genetics : EJHG · 2016Article
- Joint analysis of multiple blood pressure phenotypes in GAW19 data by using a multivariate rare-variant association test.BMC proceedings · 2016Article
- Next Generation Mapping of Enological Traits in an F2 Interspecific Grapevine Hybrid Family.PloS one · 2016Article
- A nonparametric method to test for associations between rare variants and multiple traits.Genetics research · 2016Article
- Associating Multivariate Quantitative Phenotypes with Genetic Variants in Family Samples with a Novel Kernel Machine Regression Method.Genetics · 2015Article
- An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.Genetic epidemiology · 2015Article
- ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.Communications for statistical applications and methods · 2015Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
In studies of complex disorders such as nicotine dependence, it is common that researchers assess multiple variables related to a disorder as well as other disorders that are potentially correlated with the primary disorder of interest. In this work, we refer to those variables and disorders broadly as multiple traits. The multiple traits may or may not have a common causal genetic variant. Intuitively, it may be more powerful to accommodate multiple traits in genetic traits, but the analysis of multiple traits is generally more complicated than the analysis of a single trait. Furthermore, it is not well documented as to how much power we may potentially gain by considering multiple traits. Our aim is to enhance our understanding on this important and practical issue. We considered a variety of correlation structures between traits and the disease locus. To focus on the effect of accommodating multiple traits, we examined genetic models that are relatively simple so that we can pinpoint the factors affecting the power. We conducted simulation studies to explore the performance of testing multiple traits simultaneously and the performance of testing a single trait at a time in family-based association studies. Our simulation results demonstrated that the performance of testing multiple traits simultaneously is better than that of testing each trait individually for almost models considered. We also found that the power of association tests varies among the underlying models. The advantage of conducting a multiple traits test is minimized when some traits are influenced by the gene only through other traits; and it is maximized when there are causal relations between the traits and the gene, and among the traits themselves or when there are extraneous traits.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.